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» Policy Gradient Methods for Robotics
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ATAL
2005
Springer
14 years 1 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
ICRA
2009
IEEE
169views Robotics» more  ICRA 2009»
14 years 2 months ago
Manipulation planning with Workspace Goal Regions
— We present an approach to path planning for manipulators that uses Workspace Goal Regions (WGRs) to specify goal end-effector poses. Instead of specifying a discrete set of goa...
Dmitry Berenson, Siddhartha S. Srinivasa, Dave Fer...
ICRA
2007
IEEE
178views Robotics» more  ICRA 2007»
14 years 2 months ago
Behavior Based Adaptive Control for Autonomous Oceanographic Sampling
Abstract— This paper describes an investigation into the adaptive control of autonomous mobile sensor platforms for providing oceanographic sampling. Mobile sensor platforms prov...
Donald P. Eickstedt, Michael R. Benjamin, Ding Wan...
ML
2006
ACM
13 years 7 months ago
Universal parameter optimisation in games based on SPSA
Most game programs have a large number of parameters that are crucial for their performance. While tuning these parameters by hand is rather difficult, efficient and easy to use ge...
Levente Kocsis, Csaba Szepesvári
NIPS
2008
13 years 9 months ago
Bayesian Kernel Shaping for Learning Control
In kernel-based regression learning, optimizing each kernel individually is useful when the data density, curvature of regression surfaces (or decision boundaries) or magnitude of...
Jo-Anne Ting, Mrinal Kalakrishnan, Sethu Vijayakum...